Coupled Skin–Muscle-Inspired Potential Fields for Mapless Multi-Robot Formation Navigation

Multi-robot formations can extend sensing coverage and improve operational resilience, but their practical value depends on coordinated navigation through cluttered environments. Under mapless local sensing, existing methods face conflicting demands for obstacle avoidance, collective progress and formation recovery. This study presents Coupled ESRM–MFAM, a deterministic bio-inspired controller for six differential-drive robots. An Elastic Skin Reflex Model (ESRM) provides local obstacle-surface response, while a Muscle Fibre Actuation Model (MFAM) generates collective driving forces. Their direct combination, together with teammate-safety handling, integrates environmental response and formation coordination within a local control loop. Across 800 geometry-certified environments, the controller achieved a task completion rate of 75.00% within 120 s, compared with 56.50% for VFH+, the strongest tested baseline adaptation. This advantage remained significant after Holm correction and was reproduced on a separately generated 400-environment evaluation set. Component ablations supported the contributions of environmental response, collective actuation and teammate safety to timely completion. ROS2/Gazebo measurements further showed that six-robot controller computation remained within the budget required for 10 Hz control. These results support coupled environmental response and collective actuation as a practical approach to timely formation navigation under the tested local-sensing conditions.